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OpenSearch Consultant - May 2026
Remote, RemoteFor one of our clients in the fashion industry, we are looking for a freelance OpenSearch Consultant – May 2026
Overview:
Background:
The company is developing a next-generation, AI-driven on-site search and PLP-ranking capability. Several critical elements require specialized expertise in:
Tasks:
Location: 100% Remote
Start: 11.05.2026
Duration: till 31/12/2026
Capacity: ~36 hours per week
Overview:
- Creation of an in-house solution for on-site search along with a Merchandising UI.
- The project aims to replace the current keyword-driven external solution for on-site search with an AI-driven solution featuring semantic understanding and personalization capabilities.
- The services mentioned in point 3 will be delivered within the framework of the agile development method Scrum.
Background:
The company is developing a next-generation, AI-driven on-site search and PLP-ranking capability. Several critical elements require specialized expertise in:
- OpenSearch relevance engineering
- Multimodal product embeddings
- Semantic search optimization
- Personalization models
- LLM-based query processing
- Hybrid lexical/semantic retrieval
- Multilingual search infrastructure
Tasks:
- Technical consultation, configuration, and optimization of OpenSearch-based search relevance components, including analyzers, scoring parameters, hybrid retrieval structures, and vector-search integrations.
- Development and refinement of retrieval and ranking models, including multi-stage ranking approaches, learning-to-rank concepts, and integration of relevance, behavioral, and business signals into ranking pipelines.
- Creation of multilingual NLP components for various locales (LAM, EU, NAM), including tokenization, stemming, normalization, and locale-specific linguistic processing within OpenSearch and related pipelines.
- Design and implementation of query understanding mechanisms, including synonym and concept extraction based on catalog and interaction data, query intent interpretation methods, and term/concept expansion techniques.
- Development of LLM-enhanced search components, including prompt construction and incorporation of LLM-derived semantic signals into retrieval and ranking logic.
- Creation of personalization logic for search and PLP ranking, including re-ranking frameworks balancing user affinity, semantic relevance, and commercial parameters.
- Development and validation of autocomplete, spelling correction, and search suggestion components, ensuring robust multilingual handling and adherence to domain-specific terminology.
- Definition and refinement of commercial relevance models, including recency-weighted popularity signals, interaction-based relevance indicators, and business-driven ranking adjustments.
- Construction of evaluation and diagnostic frameworks for relevance quality using offline IR metrics and analytical assessment methods.
- Modeling and integration of real-time or near-real-time data signals (e.g., stock levels, size availability) into filtering, faceting, and ranking components.
- Technical implementation of data-science-driven backend logic for the Merchandising UI, including scoring routines, rule evaluation structures, configurable business logic, and interfaces for merchandising adjustments to search and ranking behavior
Location: 100% Remote
Start: 11.05.2026
Duration: till 31/12/2026
Capacity: ~36 hours per week